THE RELATIONSHIP OF COMPONENTS OF MINDFULNESS WITH COGNITIVE EMOTION REGULATION STRATEGIES: THE MEDIATING ROLE OF ALEXITHYMIA
Bibliographic record
Abstract
Introduction: The aim of this study was to investigate the causal relationship of mindfulness and cognitive emotion regulation strategies and mediating role of alexithymia in this relationship. Method: In this descriptive-correlational study, 355 students (192 femalesand 163 males) were recruited from ShahidBahonar university of Kerman through randomclustered sampling method. Five- facet mindfulness questionnaire (FFMQ), Toronto alexithymia scale (TAS) and cognitive emotion regulation strategies questionnaire (CERQ) were used as instruments. Data were analyzed through SPSS22 and Mplus5 software packages and using path analysis and mediation analysis. Results: There was significant relationship between facets of mindfulness, alexithymia and cognitive emotion regulation strategies. In addition, facet of difficulty in identifying feelings had partial mediating role in relationship between facets of mindfulness and positive emotion regulation strategies. Conclusion: Results indicated that mindfulness has a significant role in prediction of different aspects of alexithymia and cognitive emotion regulation and it can be useful for improvement of emotional problems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".